1. Field of Invention
The present invention relates to energy signal detection, and more particularly to a process and system of energy signal detection that can minimizes false alarms and maximize the sensitivity, performance and reliability of the energy signal detection.
2. Description of Related Arts
The great number of false alarms is causing the security industry to loose credibility with government and private enforcement agencies. A trend of no response policies and heavy fines for false alarms is in place already for many jurisdictions. Some false alarms are user related, but the majority of false alarms originate from Passive Infra Red (PIR) detectors, most of which in use today are low end, low cost units.
A motion detector is a kind of energy signal detection device which utilizes Passive Infra-Red (PIR) technology to detect movement of body heat to activate the alarm in the event of an intrusion. The conventional motion sensor, such as PIR detector, usually comprises a sensor casing, a sensing element, a lens directing infrared energy onto the sensing element so as to detect a movement of a physical object within a detecting area, and a decision making circuit (which may comprise of an analog-to-digital converter) for compiling an electrical signal which is outputted from the sensing element so as to recognize the physical movement in the detecting area.
A typical conventional energy signal detector uses a pyroelectric sensing module as the sensing element that has a very low analog signal level output. A low but still usable AC signal is in the order of 1 to 2 mVp-p with a much larger ˜10 mVp-p of high frequency noise component, all of which rides on a DC component of 400 mV to 2000 mV, that will change with temperature, aging and also part to part. The usable frequency component of this signal is from 0.1 Hz to 10 Hz. The lens directs infrared energy onto this sensing element. The sensing element's output is traditionally fed into a tight band pass filter stage to reduce high frequency noise and strip the DC element that the signal rides on. It is then fed into a high gain stage (typically ˜72 db) so that the signal can be used by either discreet components or by a microcontroller to make decisions and act upon them.
A drawback of the traditional energy signal detector is the filter and gain stages. By filtering the signal, it also removes information that is sometimes critical to being able to make a reliable decision. Any signal discontinuity between the sensing element and the filter stage due to external electrical factors or forces will look no different then a low level infrared energy signature at the output of the gain stage. This impacts the energy signal detector's maximum range and pet immunity reliability. The typical information processing methods available after these stages are to do root mean squared energy under the curve analysis or similar, to determine if the energy exceeds a threshold limit. Older detecting processors do not have the processing power for more elegant techniques to be used. There is also a frequency component as well. It will vary from 0.1 Hz to 10 Hz and change with movement. There is often not even a single full cycle of any given frequency to use.
With such limitations due to the signal pre-conditioning, almost all conventional energy signal detectors include a “pulse count” feature that basically admits that the energy signal detector can false under normal operating conditions. Higher end, more expensive, energy signal detectors can include a secondary sensing method (such as a micro wave sensor) where it needs one technology to confirm the other in the decision making process.
More specifically, the pyroelectric sensing module usually comprises a signal input to receive an infrared signal created by infrared energy of a moving target, for example, in the detecting area, a signal output adapted for producing a predetermined level of output signal in response to the infrared signal, wherein the output signal is fed into the decision making circuit for further analysis for recognizing the physical movement of the moving target in the detecting area.
A major problem for the conventional energy signal detector, especially a motion detector, is that the output signal of the pyroelectric sensing module (+DC offset) is very low, typically in the order of milli-volts, so that the output signal corresponding with actual physical movement within the detecting area is easily superseded by surrounding noise or other factors which may affect the infrared energy received by the pyroelectric sensing module. As a result, the overall performance of the conventional motion sensor will be limited.
In order to overcome this problem, the motion detector may further comprise a signal filtering circuitry and a signal amplifying circuitry electrically connected with the pyroelectric sensing module, wherein the output signals of the pyroelectric sensing module are fed into the signal filtering circuitry and the signal amplifying circuitry which are arranged to filter noise signals and amplify the remaining signals respectively for further processing of the output signals of the pyroelectric sensing module. Therefore, some signals are removed from the output signals when they have passed through the signal filtering circuitry and the signal amplifying circuitry.
A persistent problem with such signal filtering and signal amplifying strategies is that some signals which reflect the actual physical movement, as opposed to surrounding noise, may be mistakenly removed by the signal filtering circuitry so that the real or actual physical movements within the detecting area may not be successfully detected. On the other hand, those output signals which reflect surrounding noise or any other environmental factors may be mistakenly interpreted as an actual physical movement in the detecting area so that false alarms may be generated as a result.
One way to overcome these design limitations is to feed the signals directly into a DSP processor. A DSP processor is capable of working very well with low signal levels and high frequency components. Aside from significant cost increases with this approach, it still has its technical drawbacks as well. For example, the DSP consumes higher power than what is typically allotted for a PIR design.
A DSP processor is designed to work on signals in the frequency domain. It is uniquely tailored to be able to accomplish Fourier math analysis of signals at high frequencies. The problem here is this signal exists predominantly in the time domain. There is no consistent signal frequency to analyze. Also the slower in frequency the signal is, the more storage and horsepower will be required by the processor to be able to detect it. One would want to digitally filter the high frequency noise component so as to detect discontinuities. This means that it needs to sample for durations of time in the order of seconds to be able to detect the low frequency signal required. This then becomes as issue for storage of the samples to be worked on. Increasing the storage, results in increasing the cost yet again.